Mobile Computing - Introduction to the Special Theme

The articles presented in this issue reflect the many faces of our special theme, “Mobile computing”, and address topics including: Mobile service platforms and new ways of establishing networks, privacy concerns and security challenges, location services and collaborative data capture.

The invited article by Engin Kirda summarizes a research project that focuses on Android malware detection. Matthias Steinbauer et al discuss effects of the convergence of cloud and mobile computing. Francisco Barcelo-Arroyo et al present results related to the important topic of providing indoor localization through the combined use of communication networks.

Different kinds of computing services form the focus of the first six articles:

Folino and Pisani describe a framework for generating decision tree-based models that use evolutionary algorithms to take automatic decisions regarding the offloading of mobile applications into a cloud environment. Larkou et al present SmartLab, an open IaaS cloud of smartphones that improves the efficiency of systems-oriented mobile computing research.

Mobile device networks also offer enormous potential for data mining. Comito et al have defined a distributed architecture with an energy-aware scheduling strategy that assigns data mining tasks in a peer-to-peer network of mobile devices.

Adelsberger and Tröster present a means of using smartphones to synchronize and control sensors wirelessly, more effectively, and in a more energy-efficient way than is usually the case for wireless synchronizing of multiple data streams.

With mobile Internet on the rise, the demand for wireless networks is growing at an unprecedented pace. Hoekstra and van der Mei describe new methods, developed in the Netherlands, that use smart algorithms to split traffic over the numerous overlapping networks in the country, thereby increasing wireless speed.

Moving towards the viewpoint of the user, Jacobsson et al describe a design concept for changing setups and user interface styles of smartphones by physically attaching phone shells or accessories such as jewellery or headphones to the device, enabling quick shifts between, for example, business and leisure modes.

The user perspective is also present in different mobile service platforms. The near ubiquity of smartphones makes them ideally suited for transport planning services. Capra et al introduce the TravelDashboard project, which will allow customizable trip planning according to personal preferences, also incorporating user-generated content with information on issues such as crowdedness of buses. In the same vein, Cuesta et al’s CoMobility platform also allows travel planning but integrates carpooling with public transportation. Wac focuses on a Quality of Service Information System and reports on a mobile application that uses measurement data provided by mobile users to predict a network’s expected performance.

Conti et al discuss opportunistic computing, a self-organizing dynamic networking paradigm that combines pervasive environmental network devices with mobile devices to allow communication and services. They present the CAMEO middleware platform, which focuses on the management and elaboration of context information in such opportunistic networks.

The pervasiveness of mobile devices has raised interest in collecting their sensor data via “crowd sensing”. Haderer et al address the needs of various research communities with their APISENSE platform, which gives researchers an online environment in which they can set up an experiment without in-depth technical knowledge while ensuring the privacy and security of the participants collecting the data.

Privacy and security are, indeed, important issues as consumers and companies enter the world of mobile computing with unprecedented enthusiasm, and a number of contributions in this issue are dedicated to them.
One reason for the widespread use of mobile devices is, of course, the wide availability of Wi-Fi networks. Transmitting data over unsecured networks has well-known risks, but Cunche et al. go further and show how the automatic search for networks enabled on most smartphones can be used to not only fingerprint individual devices, but also to identify social links between their owners.

Networked calendars and other collaborative applications are very popular but pose considerable security challenges. Imine and Rusinowitch have developed a decentralized and secure shared calendar that is independent of third-party servers, instead allowing users to share their calendar events in dynamic groups in ad-hoc networks.

Constantino et al present an implementation of the cryptographic FairPlay framework for Android smartphones. It protects users’ privacy in opportunistic networks by ensuring that information is exchanged with other users’ devices via Bluetooth only if they have matching interest profiles, which can be determined without sending sensitive information in plaintext.

Achara et al have examined the information that can be gained from smartphones to educate users about risks. The Mobilitics project investigates both the Android and iOS operating systems and apps for these platforms for potential privacy leaks and has found that many apps access information not necessary for their operation.

One way of making apps more secure can be found in Costa et al’s proposal for a security-enabled app marketplace, where applications are analyzed to ensure that they comply with the security policy and can be installed without affecting the device’s security configuration.

While GPS-based localization offers a multitude of location-based services (eg, navigation) in outdoor environments, indoor mobile environments require different approaches, some of which are presented in the next three contributions.

Laoudias et al’s Airplace indoor positioning system uses a radiomap built from received signal strength (RSS) fingerprints. This radiomap is transmitted to the user’s Android smartphone upon entering the building and allows the device to determine its position based on the signal strength it receives from surrounding wireless access points without revealing its personal state.

RSS fingerprinting is also one of the three techniques that are combined in the user localization method presented by Ševčík, the others being dead reckoning and sequential Monte Carlo filtering. The prototype displays the position of the user on a floor plan. Further developments are planned to allow navigation to a selected point on the map and augmented reality.

Afyouni et al focus on the representation and management of spatial data and location-dependent query processing required for the development of efficient and flexible context-aware indoor navigation systems. They developed a hierarchical data model of an indoor environment and algorithms that utilize it to process location-dependent queries continuously and effectively.

Finally, we have four contributions dedicated to applications. From bus travel to oil spills, they present four innovative uses of mobile computing combined with crowdsourcing. While Falcao e Cunha et al present their MOVE-ME multimodal travel planning project with user contribution, Segrelles et al’s TRENCADIS allows the secure sharing, organization and searching of medical images on mobile devices and has been prototyped for breast cancer diagnosis and treatment.

The papers by Trigueros et al. and Martinelli et al both present applications for environmental monitoring with a strong focus on crowdsourcing: Trigueros and Peinado’s U-AirPoll is a novel approach to distributed and collaborative air quality measurement, while Martinelli et al.’s ARGO Sentinel allows volunteers at sea to immediately report sighted oil spillages.